Cross-Lingual Argumentative Relation Identification: from English to Portuguese

Gil Rocha, Christian Stab, Henrique Lopes Cardoso, Iryna Gurevych


Abstract
Argument mining aims to detect and identify argument structures from textual resources. In this paper, we aim to address the task of argumentative relation identification, a subtask of argument mining, for which several approaches have been recently proposed in a monolingual setting. To overcome the lack of annotated resources in less-resourced languages, we present the first attempt to address this subtask in a cross-lingual setting. We compare two standard strategies for cross-language learning, namely: projection and direct-transfer. Experimental results show that by using unsupervised language adaptation the proposed approaches perform at a competitive level when compared with fully-supervised in-language learning settings.
Anthology ID:
W18-5217
Volume:
Proceedings of the 5th Workshop on Argument Mining
Month:
November
Year:
2018
Address:
Brussels, Belgium
Venues:
ArgMining | EMNLP | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
144–154
Language:
URL:
https://www.aclweb.org/anthology/W18-5217
DOI:
10.18653/v1/W18-5217
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PDF:
http://aclanthology.lst.uni-saarland.de/W18-5217.pdf